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Unverified Commit e93735a2 authored by MissPenguin's avatar MissPenguin Committed by GitHub
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Merge pull request #3083 from WenmuZhou/table1 

[DO NOT MERGE]Table
parents 6127aad9 b2260182
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MANIFEST.in
View file @ e93735a2
include LICENSE.txt include LICENSE
include README.md include README.md
recursive-include ppocr/utils *.txt utility.py logging.py recursive-include ppocr/utils *.txt utility.py logging.py network.py
recursive-include ppocr/data/ *.py recursive-include ppocr/data/ *.py
recursive-include ppocr/postprocess *.py recursive-include ppocr/postprocess *.py
recursive-include tools/infer *.py recursive-include tools/infer *.py
......
doc/doc_ch/whl.md
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...@@ -355,3 +355,4 @@ im_show.save('result.jpg') ...@@ -355,3 +355,4 @@ im_show.save('result.jpg')
| det | 前向时使用启动检测 | TRUE | | det | 前向时使用启动检测 | TRUE |
| rec | 前向时是否启动识别 | TRUE | | rec | 前向时是否启动识别 | TRUE |
| cls | 前向时是否启动分类 (命令行模式下使用use_angle_cls控制前向是否启动分类) | FALSE | | cls | 前向时是否启动分类 (命令行模式下使用use_angle_cls控制前向是否启动分类) | FALSE |
| show_log | 是否打印det和rec等信息 | FALSE |
doc/doc_en/whl_en.md
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...@@ -362,3 +362,5 @@ im_show.save('result.jpg') ...@@ -362,3 +362,5 @@ im_show.save('result.jpg')
| det | Enable detction when `ppocr.ocr` func exec | TRUE | | det | Enable detction when `ppocr.ocr` func exec | TRUE |
| rec | Enable recognition when `ppocr.ocr` func exec | TRUE | | rec | Enable recognition when `ppocr.ocr` func exec | TRUE |
| cls | Enable classification when `ppocr.ocr` func exec((Use use_angle_cls in command line mode to control whether to start classification in the forward direction) | FALSE | | cls | Enable classification when `ppocr.ocr` func exec((Use use_angle_cls in command line mode to control whether to start classification in the forward direction) | FALSE |
| show_log | Whether to print log in det and rec
| FALSE |
\ No newline at end of file
paddleocr.py
View file @ e93735a2
...@@ -19,17 +19,16 @@ __dir__ = os.path.dirname(__file__) ...@@ -19,17 +19,16 @@ __dir__ = os.path.dirname(__file__)
sys.path.append(os.path.join(__dir__, '')) sys.path.append(os.path.join(__dir__, ''))
import cv2 import cv2
import logging
import numpy as np import numpy as np
from pathlib import Path from pathlib import Path
import tarfile
import requests
from tqdm import tqdm
from tools.infer import predict_system from tools.infer import predict_system
from ppocr.utils.logging import get_logger from ppocr.utils.logging import get_logger
logger = get_logger() logger = get_logger()
from ppocr.utils.utility import check_and_read_gif, get_image_file_list from ppocr.utils.utility import check_and_read_gif, get_image_file_list
from ppocr.utils.network import maybe_download, download_with_progressbar, is_link, confirm_model_dir_url
from tools.infer.utility import draw_ocr, init_args, str2bool from tools.infer.utility import draw_ocr, init_args, str2bool
__all__ = ['PaddleOCR'] __all__ = ['PaddleOCR']
...@@ -37,84 +36,84 @@ __all__ = ['PaddleOCR'] ...@@ -37,84 +36,84 @@ __all__ = ['PaddleOCR']
model_urls = { model_urls = {
'det': { 'det': {
'ch': 'ch':
'https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_infer.tar', 'https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_infer.tar',
'en': 'en':
'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/en_ppocr_mobile_v2.0_det_infer.tar' 'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/en_ppocr_mobile_v2.0_det_infer.tar'
}, },
'rec': { 'rec': {
'ch': { 'ch': {
'url': 'url':
'https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_infer.tar', 'https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_infer.tar',
'dict_path': './ppocr/utils/ppocr_keys_v1.txt' 'dict_path': './ppocr/utils/ppocr_keys_v1.txt'
}, },
'en': { 'en': {
'url': 'url':
'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/en_number_mobile_v2.0_rec_infer.tar', 'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/en_number_mobile_v2.0_rec_infer.tar',
'dict_path': './ppocr/utils/en_dict.txt' 'dict_path': './ppocr/utils/en_dict.txt'
}, },
'french': { 'french': {
'url': 'url':
'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/french_mobile_v2.0_rec_infer.tar', 'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/french_mobile_v2.0_rec_infer.tar',
'dict_path': './ppocr/utils/dict/french_dict.txt' 'dict_path': './ppocr/utils/dict/french_dict.txt'
}, },
'german': { 'german': {
'url': 'url':
'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/german_mobile_v2.0_rec_infer.tar', 'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/german_mobile_v2.0_rec_infer.tar',
'dict_path': './ppocr/utils/dict/german_dict.txt' 'dict_path': './ppocr/utils/dict/german_dict.txt'
}, },
'korean': { 'korean': {
'url': 'url':
'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/korean_mobile_v2.0_rec_infer.tar', 'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/korean_mobile_v2.0_rec_infer.tar',
'dict_path': './ppocr/utils/dict/korean_dict.txt' 'dict_path': './ppocr/utils/dict/korean_dict.txt'
}, },
'japan': { 'japan': {
'url': 'url':
'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/japan_mobile_v2.0_rec_infer.tar', 'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/japan_mobile_v2.0_rec_infer.tar',
'dict_path': './ppocr/utils/dict/japan_dict.txt' 'dict_path': './ppocr/utils/dict/japan_dict.txt'
}, },
'chinese_cht': { 'chinese_cht': {
'url': 'url':
'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/chinese_cht_mobile_v2.0_rec_infer.tar', 'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/chinese_cht_mobile_v2.0_rec_infer.tar',
'dict_path': './ppocr/utils/dict/chinese_cht_dict.txt' 'dict_path': './ppocr/utils/dict/chinese_cht_dict.txt'
}, },
'ta': { 'ta': {
'url': 'url':
'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/ta_mobile_v2.0_rec_infer.tar', 'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/ta_mobile_v2.0_rec_infer.tar',
'dict_path': './ppocr/utils/dict/ta_dict.txt' 'dict_path': './ppocr/utils/dict/ta_dict.txt'
}, },
'te': { 'te': {
'url': 'url':
'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/te_mobile_v2.0_rec_infer.tar', 'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/te_mobile_v2.0_rec_infer.tar',
'dict_path': './ppocr/utils/dict/te_dict.txt' 'dict_path': './ppocr/utils/dict/te_dict.txt'
}, },
'ka': { 'ka': {
'url': 'url':
'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/ka_mobile_v2.0_rec_infer.tar', 'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/ka_mobile_v2.0_rec_infer.tar',
'dict_path': './ppocr/utils/dict/ka_dict.txt' 'dict_path': './ppocr/utils/dict/ka_dict.txt'
}, },
'latin': { 'latin': {
'url': 'url':
'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/latin_ppocr_mobile_v2.0_rec_infer.tar', 'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/latin_ppocr_mobile_v2.0_rec_infer.tar',
'dict_path': './ppocr/utils/dict/latin_dict.txt' 'dict_path': './ppocr/utils/dict/latin_dict.txt'
}, },
'arabic': { 'arabic': {
'url': 'url':
'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/arabic_ppocr_mobile_v2.0_rec_infer.tar', 'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/arabic_ppocr_mobile_v2.0_rec_infer.tar',
'dict_path': './ppocr/utils/dict/arabic_dict.txt' 'dict_path': './ppocr/utils/dict/arabic_dict.txt'
}, },
'cyrillic': { 'cyrillic': {
'url': 'url':
'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/cyrillic_ppocr_mobile_v2.0_rec_infer.tar', 'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/cyrillic_ppocr_mobile_v2.0_rec_infer.tar',
'dict_path': './ppocr/utils/dict/cyrillic_dict.txt' 'dict_path': './ppocr/utils/dict/cyrillic_dict.txt'
}, },
'devanagari': { 'devanagari': {
'url': 'url':
'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/devanagari_ppocr_mobile_v2.0_rec_infer.tar', 'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/devanagari_ppocr_mobile_v2.0_rec_infer.tar',
'dict_path': './ppocr/utils/dict/devanagari_dict.txt' 'dict_path': './ppocr/utils/dict/devanagari_dict.txt'
} }
}, },
'cls': 'cls':
'https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_infer.tar' 'https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_infer.tar'
} }
SUPPORT_DET_MODEL = ['DB'] SUPPORT_DET_MODEL = ['DB']
...@@ -123,50 +122,6 @@ SUPPORT_REC_MODEL = ['CRNN'] ...@@ -123,50 +122,6 @@ SUPPORT_REC_MODEL = ['CRNN']
BASE_DIR = os.path.expanduser("~/.paddleocr/") BASE_DIR = os.path.expanduser("~/.paddleocr/")
def download_with_progressbar(url, save_path):
response = requests.get(url, stream=True)
total_size_in_bytes = int(response.headers.get('content-length', 0))
block_size = 1024 # 1 Kibibyte
progress_bar = tqdm(total=total_size_in_bytes, unit='iB', unit_scale=True)
with open(save_path, 'wb') as file:
for data in response.iter_content(block_size):
progress_bar.update(len(data))
file.write(data)
progress_bar.close()
if total_size_in_bytes == 0 or progress_bar.n != total_size_in_bytes:
logger.error("Something went wrong while downloading models")
sys.exit(0)
def maybe_download(model_storage_directory, url):
# using custom model
tar_file_name_list = [
'inference.pdiparams', 'inference.pdiparams.info', 'inference.pdmodel'
]
if not os.path.exists(
os.path.join(model_storage_directory, 'inference.pdiparams')
) or not os.path.exists(
os.path.join(model_storage_directory, 'inference.pdmodel')):
tmp_path = os.path.join(model_storage_directory, url.split('/')[-1])
print('download {} to {}'.format(url, tmp_path))
os.makedirs(model_storage_directory, exist_ok=True)
download_with_progressbar(url, tmp_path)
with tarfile.open(tmp_path, 'r') as tarObj:
for member in tarObj.getmembers():
filename = None
for tar_file_name in tar_file_name_list:
if tar_file_name in member.name:
filename = tar_file_name
if filename is None:
continue
file = tarObj.extractfile(member)
with open(
os.path.join(model_storage_directory, filename),
'wb') as f:
f.write(file.read())
os.remove(tmp_path)
def parse_args(mMain=True): def parse_args(mMain=True):
import argparse import argparse
parser = init_args() parser = init_args()
...@@ -194,10 +149,12 @@ class PaddleOCR(predict_system.TextSystem): ...@@ -194,10 +149,12 @@ class PaddleOCR(predict_system.TextSystem):
args: args:
**kwargs: other params show in paddleocr --help **kwargs: other params show in paddleocr --help
""" """
postprocess_params = parse_args(mMain=False) params = parse_args(mMain=False)
postprocess_params.__dict__.update(**kwargs) params.__dict__.update(**kwargs)
self.use_angle_cls = postprocess_params.use_angle_cls if not params.show_log:
lang = postprocess_params.lang logger.setLevel(logging.INFO)
self.use_angle_cls = params.use_angle_cls
lang = params.lang
latin_lang = [ latin_lang = [
'af', 'az', 'bs', 'cs', 'cy', 'da', 'de', 'es', 'et', 'fr', 'ga', 'af', 'az', 'bs', 'cs', 'cy', 'da', 'de', 'es', 'et', 'fr', 'ga',
'hr', 'hu', 'id', 'is', 'it', 'ku', 'la', 'lt', 'lv', 'mi', 'ms', 'hr', 'hu', 'id', 'is', 'it', 'ku', 'la', 'lt', 'lv', 'mi', 'ms',
...@@ -223,46 +180,45 @@ class PaddleOCR(predict_system.TextSystem): ...@@ -223,46 +180,45 @@ class PaddleOCR(predict_system.TextSystem):
lang = "devanagari" lang = "devanagari"
assert lang in model_urls[ assert lang in model_urls[
'rec'], 'param lang must in {}, but got {}'.format( 'rec'], 'param lang must in {}, but got {}'.format(
model_urls['rec'].keys(), lang) model_urls['rec'].keys(), lang)
if lang == "ch": if lang == "ch":
det_lang = "ch" det_lang = "ch"
else: else:
det_lang = "en" det_lang = "en"
use_inner_dict = False use_inner_dict = False
if postprocess_params.rec_char_dict_path is None: if params.rec_char_dict_path is None:
use_inner_dict = True use_inner_dict = True
postprocess_params.rec_char_dict_path = model_urls['rec'][lang][ params.rec_char_dict_path = model_urls['rec'][lang][
'dict_path'] 'dict_path']
# init model dir # init model dir
if postprocess_params.det_model_dir is None: params.det_model_dir, det_url = confirm_model_dir_url(params.det_model_dir,
postprocess_params.det_model_dir = os.path.join(BASE_DIR, VERSION, os.path.join(BASE_DIR, VERSION, 'det', det_lang),
'det', det_lang) model_urls['det'][det_lang])
if postprocess_params.rec_model_dir is None: params.rec_model_dir, rec_url = confirm_model_dir_url(params.rec_model_dir,
postprocess_params.rec_model_dir = os.path.join(BASE_DIR, VERSION, os.path.join(BASE_DIR, VERSION, 'rec', lang),
'rec', lang) model_urls['rec'][lang]['url'])
if postprocess_params.cls_model_dir is None: params.cls_model_dir, cls_url = confirm_model_dir_url(params.cls_model_dir,
postprocess_params.cls_model_dir = os.path.join(BASE_DIR, 'cls') os.path.join(BASE_DIR, VERSION, 'cls'),
print(postprocess_params) model_urls['cls'])
# download model # download model
maybe_download(postprocess_params.det_model_dir, maybe_download(params.det_model_dir, det_url)
model_urls['det'][det_lang]) maybe_download(params.rec_model_dir, rec_url)
maybe_download(postprocess_params.rec_model_dir, maybe_download(params.cls_model_dir, cls_url)
model_urls['rec'][lang]['url'])
maybe_download(postprocess_params.cls_model_dir, model_urls['cls'])
if postprocess_params.det_algorithm not in SUPPORT_DET_MODEL: if params.det_algorithm not in SUPPORT_DET_MODEL:
logger.error('det_algorithm must in {}'.format(SUPPORT_DET_MODEL)) logger.error('det_algorithm must in {}'.format(SUPPORT_DET_MODEL))
sys.exit(0) sys.exit(0)
if postprocess_params.rec_algorithm not in SUPPORT_REC_MODEL: if params.rec_algorithm not in SUPPORT_REC_MODEL:
logger.error('rec_algorithm must in {}'.format(SUPPORT_REC_MODEL)) logger.error('rec_algorithm must in {}'.format(SUPPORT_REC_MODEL))
sys.exit(0) sys.exit(0)
if use_inner_dict: if use_inner_dict:
postprocess_params.rec_char_dict_path = str( params.rec_char_dict_path = str(
Path(__file__).parent / postprocess_params.rec_char_dict_path) Path(__file__).parent / params.rec_char_dict_path)
print(params)
# init det_model and rec_model # init det_model and rec_model
super().__init__(postprocess_params) super().__init__(params)
def ocr(self, img, det=True, rec=True, cls=True): def ocr(self, img, det=True, rec=True, cls=True):
""" """
...@@ -320,7 +276,7 @@ def main(): ...@@ -320,7 +276,7 @@ def main():
# for cmd # for cmd
args = parse_args(mMain=True) args = parse_args(mMain=True)
image_dir = args.image_dir image_dir = args.image_dir
if image_dir.startswith('http'): if is_link(image_dir):
download_with_progressbar(image_dir, 'tmp.jpg') download_with_progressbar(image_dir, 'tmp.jpg')
image_file_list = ['tmp.jpg'] image_file_list = ['tmp.jpg']
else: else:
......
ppocr/data/imaug/__init__.py
View file @ e93735a2
...@@ -29,6 +29,7 @@ from .label_ops import * ...@@ -29,6 +29,7 @@ from .label_ops import *
from .east_process import * from .east_process import *
from .sast_process import * from .sast_process import *
from .pg_process import * from .pg_process import *
from .gen_table_mask import *
def transform(data, ops=None): def transform(data, ops=None):
......
ppocr/data/imaug/gen_table_mask.py 0 → 100644
View file @ e93735a2
"""
# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from __future__ import unicode_literals
import sys
import six
import cv2
import numpy as np
class GenTableMask(object):
""" gen table mask """
def __init__(self, shrink_h_max, shrink_w_max, mask_type=0, **kwargs):
self.shrink_h_max = 5
self.shrink_w_max = 5
self.mask_type = mask_type
def projection(self, erosion, h, w, spilt_threshold=0):
# 水平投影
projection_map = np.ones_like(erosion)
project_val_array = [0 for _ in range(0, h)]
for j in range(0, h):
for i in range(0, w):
if erosion[j, i] == 255:
project_val_array[j] += 1
# 根据数组，获取切割点
start_idx = 0 # 记录进入字符区的索引
end_idx = 0 # 记录进入空白区域的索引
in_text = False # 是否遍历到了字符区内
box_list = []
for i in range(len(project_val_array)):
if in_text == False and project_val_array[i] > spilt_threshold: # 进入字符区了
in_text = True
start_idx = i
elif project_val_array[i] <= spilt_threshold and in_text == True: # 进入空白区了
end_idx = i
in_text = False
if end_idx - start_idx <= 2:
continue
box_list.append((start_idx, end_idx + 1))
if in_text:
box_list.append((start_idx, h - 1))
# 绘制投影直方图
for j in range(0, h):
for i in range(0, project_val_array[j]):
projection_map[j, i] = 0
return box_list, projection_map
def projection_cx(self, box_img):
box_gray_img = cv2.cvtColor(box_img, cv2.COLOR_BGR2GRAY)
h, w = box_gray_img.shape
# 灰度图片进行二值化处理
ret, thresh1 = cv2.threshold(box_gray_img, 200, 255, cv2.THRESH_BINARY_INV)
# 纵向腐蚀
if h < w:
kernel = np.ones((2, 1), np.uint8)
erode = cv2.erode(thresh1, kernel, iterations=1)
else:
erode = thresh1
# 水平膨胀
kernel = np.ones((1, 5), np.uint8)
erosion = cv2.dilate(erode, kernel, iterations=1)
# 水平投影
projection_map = np.ones_like(erosion)
project_val_array = [0 for _ in range(0, h)]
for j in range(0, h):
for i in range(0, w):
if erosion[j, i] == 255:
project_val_array[j] += 1
# 根据数组，获取切割点
start_idx = 0 # 记录进入字符区的索引
end_idx = 0 # 记录进入空白区域的索引
in_text = False # 是否遍历到了字符区内
box_list = []
spilt_threshold = 0
for i in range(len(project_val_array)):
if in_text == False and project_val_array[i] > spilt_threshold: # 进入字符区了
in_text = True
start_idx = i
elif project_val_array[i] <= spilt_threshold and in_text == True: # 进入空白区了
end_idx = i
in_text = False
if end_idx - start_idx <= 2:
continue
box_list.append((start_idx, end_idx + 1))
if in_text:
box_list.append((start_idx, h - 1))
# 绘制投影直方图
for j in range(0, h):
for i in range(0, project_val_array[j]):
projection_map[j, i] = 0
split_bbox_list = []
if len(box_list) > 1:
for i, (h_start, h_end) in enumerate(box_list):
if i == 0:
h_start = 0
if i == len(box_list):
h_end = h
word_img = erosion[h_start:h_end + 1, :]
word_h, word_w = word_img.shape
w_split_list, w_projection_map = self.projection(word_img.T, word_w, word_h)
w_start, w_end = w_split_list[0][0], w_split_list[-1][1]
if h_start > 0:
h_start -= 1
h_end += 1
word_img = box_img[h_start:h_end + 1:, w_start:w_end + 1, :]
split_bbox_list.append([w_start, h_start, w_end, h_end])
else:
split_bbox_list.append([0, 0, w, h])
return split_bbox_list
def shrink_bbox(self, bbox):
left, top, right, bottom = bbox
sh_h = min(max(int((bottom - top) * 0.1), 1), self.shrink_h_max)
sh_w = min(max(int((right - left) * 0.1), 1), self.shrink_w_max)
left_new = left + sh_w
right_new = right - sh_w
top_new = top + sh_h
bottom_new = bottom - sh_h
if left_new >= right_new:
left_new = left
right_new = right
if top_new >= bottom_new:
top_new = top
bottom_new = bottom
return [left_new, top_new, right_new, bottom_new]
def __call__(self, data):
img = data['image']
cells = data['cells']
height, width = img.shape[0:2]
if self.mask_type == 1:
mask_img = np.zeros((height, width), dtype=np.float32)
else:
mask_img = np.zeros((height, width, 3), dtype=np.float32)
cell_num = len(cells)
for cno in range(cell_num):
if "bbox" in cells[cno]:
bbox = cells[cno]['bbox']
left, top, right, bottom = bbox
box_img = img[top:bottom, left:right, :].copy()
split_bbox_list = self.projection_cx(box_img)
for sno in range(len(split_bbox_list)):
split_bbox_list[sno][0] += left
split_bbox_list[sno][1] += top
split_bbox_list[sno][2] += left
split_bbox_list[sno][3] += top
for sno in range(len(split_bbox_list)):
left, top, right, bottom = split_bbox_list[sno]
left, top, right, bottom = self.shrink_bbox([left, top, right, bottom])
if self.mask_type == 1:
mask_img[top:bottom, left:right] = 1.0
data['mask_img'] = mask_img
else:
mask_img[top:bottom, left:right, :] = (255, 255, 255)
data['image'] = mask_img
return data
class ResizeTableImage(object):
def __init__(self, max_len, **kwargs):
super(ResizeTableImage, self).__init__()
self.max_len = max_len
def get_img_bbox(self, cells):
bbox_list = []
if len(cells) == 0:
return bbox_list
cell_num = len(cells)
for cno in range(cell_num):
if "bbox" in cells[cno]:
bbox = cells[cno]['bbox']
bbox_list.append(bbox)
return bbox_list
def resize_img_table(self, img, bbox_list, max_len):
height, width = img.shape[0:2]
ratio = max_len / (max(height, width) * 1.0)
resize_h = int(height * ratio)
resize_w = int(width * ratio)
img_new = cv2.resize(img, (resize_w, resize_h))
bbox_list_new = []
for bno in range(len(bbox_list)):
left, top, right, bottom = bbox_list[bno].copy()
left = int(left * ratio)
top = int(top * ratio)
right = int(right * ratio)
bottom = int(bottom * ratio)
bbox_list_new.append([left, top, right, bottom])
return img_new, bbox_list_new
def __call__(self, data):
img = data['image']
if 'cells' not in data:
cells = []
else:
cells = data['cells']
bbox_list = self.get_img_bbox(cells)
img_new, bbox_list_new = self.resize_img_table(img, bbox_list, self.max_len)
data['image'] = img_new
cell_num = len(cells)
bno = 0
for cno in range(cell_num):
if "bbox" in data['cells'][cno]:
data['cells'][cno]['bbox'] = bbox_list_new[bno]
bno += 1
data['max_len'] = self.max_len
return data
class PaddingTableImage(object):
def __init__(self, **kwargs):
super(PaddingTableImage, self).__init__()
def __call__(self, data):
img = data['image']
max_len = data['max_len']
padding_img = np.zeros((max_len, max_len, 3), dtype=np.float32)
height, width = img.shape[0:2]
padding_img[0:height, 0:width, :] = img.copy()
data['image'] = padding_img
return data
\ No newline at end of file
ppocr/data/imaug/operators.py
View file @ e93735a2
...@@ -81,7 +81,7 @@ class NormalizeImage(object): ...@@ -81,7 +81,7 @@ class NormalizeImage(object):
assert isinstance(img, assert isinstance(img,
np.ndarray), "invalid input 'img' in NormalizeImage" np.ndarray), "invalid input 'img' in NormalizeImage"
data['image'] = ( data['image'] = (
img.astype('float32') * self.scale - self.mean) / self.std img.astype('float32') * self.scale - self.mean) / self.std
return data return data
...@@ -163,7 +163,7 @@ class DetResizeForTest(object): ...@@ -163,7 +163,7 @@ class DetResizeForTest(object):
img, (ratio_h, ratio_w) img, (ratio_h, ratio_w)
""" """
limit_side_len = self.limit_side_len limit_side_len = self.limit_side_len
h, w, _ = img.shape h, w, c = img.shape
# limit the max side # limit the max side
if self.limit_type == 'max': if self.limit_type == 'max':
...@@ -174,7 +174,7 @@ class DetResizeForTest(object): ...@@ -174,7 +174,7 @@ class DetResizeForTest(object):
ratio = float(limit_side_len) / w ratio = float(limit_side_len) / w
else: else:
ratio = 1. ratio = 1.
else: elif self.limit_type == 'min':
if min(h, w) < limit_side_len: if min(h, w) < limit_side_len:
if h < w: if h < w:
ratio = float(limit_side_len) / h ratio = float(limit_side_len) / h
...@@ -182,6 +182,10 @@ class DetResizeForTest(object): ...@@ -182,6 +182,10 @@ class DetResizeForTest(object):
ratio = float(limit_side_len) / w ratio = float(limit_side_len) / w
else: else:
ratio = 1. ratio = 1.
elif self.limit_type == 'resize_long':
ratio = float(limit_side_len) / max(h,w)
else:
raise Exception('not support limit type, image ')
resize_h = int(h * ratio) resize_h = int(h * ratio)
resize_w = int(w * ratio) resize_w = int(w * ratio)
......
ppocr/postprocess/__init__.py
View file @ e93735a2
...@@ -24,7 +24,8 @@ __all__ = ['build_post_process'] ...@@ -24,7 +24,8 @@ __all__ = ['build_post_process']
from .db_postprocess import DBPostProcess from .db_postprocess import DBPostProcess
from .east_postprocess import EASTPostProcess from .east_postprocess import EASTPostProcess
from .sast_postprocess import SASTPostProcess from .sast_postprocess import SASTPostProcess
from .rec_postprocess import CTCLabelDecode, AttnLabelDecode, SRNLabelDecode, DistillationCTCLabelDecode from .rec_postprocess import CTCLabelDecode, AttnLabelDecode, SRNLabelDecode, DistillationCTCLabelDecode, \
TableLabelDecode
from .cls_postprocess import ClsPostProcess from .cls_postprocess import ClsPostProcess
from .pg_postprocess import PGPostProcess from .pg_postprocess import PGPostProcess
...@@ -33,7 +34,7 @@ def build_post_process(config, global_config=None): ...@@ -33,7 +34,7 @@ def build_post_process(config, global_config=None):
support_dict = [ support_dict = [
'DBPostProcess', 'EASTPostProcess', 'SASTPostProcess', 'CTCLabelDecode', 'DBPostProcess', 'EASTPostProcess', 'SASTPostProcess', 'CTCLabelDecode',
'AttnLabelDecode', 'ClsPostProcess', 'SRNLabelDecode', 'PGPostProcess', 'AttnLabelDecode', 'ClsPostProcess', 'SRNLabelDecode', 'PGPostProcess',
'DistillationCTCLabelDecode' 'DistillationCTCLabelDecode', 'TableLabelDecode'
] ]
config = copy.deepcopy(config) config = copy.deepcopy(config)
......
ppocr/postprocess/rec_postprocess.py
View file @ e93735a2
...@@ -44,16 +44,16 @@ class BaseRecLabelDecode(object): ...@@ -44,16 +44,16 @@ class BaseRecLabelDecode(object):
self.character_str = string.printable[:-6] self.character_str = string.printable[:-6]
dict_character = list(self.character_str) dict_character = list(self.character_str)
elif character_type in support_character_type: elif character_type in support_character_type:
self.character_str = "" self.character_str = []
assert character_dict_path is not None, "character_dict_path should not be None when character_type is {}".format( assert character_dict_path is not None, "character_dict_path should not be None when character_type is {}".format(
character_type) character_type)
with open(character_dict_path, "rb") as fin: with open(character_dict_path, "rb") as fin:
lines = fin.readlines() lines = fin.readlines()
for line in lines: for line in lines:
line = line.decode('utf-8').strip("\n").strip("\r\n") line = line.decode('utf-8').strip("\n").strip("\r\n")
self.character_str += line self.character_str.append(line)
if use_space_char: if use_space_char:
self.character_str += " " self.character_str.append(" ")
dict_character = list(self.character_str) dict_character = list(self.character_str)
else: else:
...@@ -319,3 +319,138 @@ class SRNLabelDecode(BaseRecLabelDecode): ...@@ -319,3 +319,138 @@ class SRNLabelDecode(BaseRecLabelDecode):
assert False, "unsupport type %s in get_beg_end_flag_idx" \ assert False, "unsupport type %s in get_beg_end_flag_idx" \
% beg_or_end % beg_or_end
return idx return idx
class TableLabelDecode(object):
""" """
def __init__(self,
character_dict_path,
**kwargs):
list_character, list_elem = self.load_char_elem_dict(character_dict_path)
list_character = self.add_special_char(list_character)
list_elem = self.add_special_char(list_elem)
self.dict_character = {}
self.dict_idx_character = {}
for i, char in enumerate(list_character):
self.dict_idx_character[i] = char
self.dict_character[char] = i
self.dict_elem = {}
self.dict_idx_elem = {}
for i, elem in enumerate(list_elem):
self.dict_idx_elem[i] = elem
self.dict_elem[elem] = i
def load_char_elem_dict(self, character_dict_path):
list_character = []
list_elem = []
with open(character_dict_path, "rb") as fin:
lines = fin.readlines()
substr = lines[0].decode('utf-8').strip("\n").split("\t")
character_num = int(substr[0])
elem_num = int(substr[1])
for cno in range(1, 1 + character_num):
character = lines[cno].decode('utf-8').strip("\n")
list_character.append(character)
for eno in range(1 + character_num, 1 + character_num + elem_num):
elem = lines[eno].decode('utf-8').strip("\n")
list_elem.append(elem)
return list_character, list_elem
def add_special_char(self, list_character):
self.beg_str = "sos"
self.end_str = "eos"
list_character = [self.beg_str] + list_character + [self.end_str]
return list_character
def __call__(self, preds):
structure_probs = preds['structure_probs']
loc_preds = preds['loc_preds']
if isinstance(structure_probs,paddle.Tensor):
structure_probs = structure_probs.numpy()
if isinstance(loc_preds,paddle.Tensor):
loc_preds = loc_preds.numpy()
structure_idx = structure_probs.argmax(axis=2)
structure_probs = structure_probs.max(axis=2)
structure_str, structure_pos, result_score_list, result_elem_idx_list = self.decode(structure_idx,
structure_probs, 'elem')
res_html_code_list = []
res_loc_list = []
batch_num = len(structure_str)
for bno in range(batch_num):
res_loc = []
for sno in range(len(structure_str[bno])):
text = structure_str[bno][sno]
if text in ['<td>', '<td']:
pos = structure_pos[bno][sno]
res_loc.append(loc_preds[bno, pos])
res_html_code = ''.join(structure_str[bno])
res_loc = np.array(res_loc)
res_html_code_list.append(res_html_code)
res_loc_list.append(res_loc)
return {'res_html_code': res_html_code_list, 'res_loc': res_loc_list, 'res_score_list': result_score_list,
'res_elem_idx_list': result_elem_idx_list,'structure_str_list':structure_str}
def decode(self, text_index, structure_probs, char_or_elem):
"""convert text-label into text-index.
"""
if char_or_elem == "char":
current_dict = self.dict_idx_character
else:
current_dict = self.dict_idx_elem
ignored_tokens = self.get_ignored_tokens('elem')
beg_idx, end_idx = ignored_tokens
result_list = []
result_pos_list = []
result_score_list = []
result_elem_idx_list = []
batch_size = len(text_index)
for batch_idx in range(batch_size):
char_list = []
elem_pos_list = []
elem_idx_list = []
score_list = []
for idx in range(len(text_index[batch_idx])):
tmp_elem_idx = int(text_index[batch_idx][idx])
if idx > 0 and tmp_elem_idx == end_idx:
break
if tmp_elem_idx in ignored_tokens:
continue
char_list.append(current_dict[tmp_elem_idx])
elem_pos_list.append(idx)
score_list.append(structure_probs[batch_idx, idx])
elem_idx_list.append(tmp_elem_idx)
result_list.append(char_list)
result_pos_list.append(elem_pos_list)
result_score_list.append(score_list)
result_elem_idx_list.append(elem_idx_list)
return result_list, result_pos_list, result_score_list, result_elem_idx_list
def get_ignored_tokens(self, char_or_elem):
beg_idx = self.get_beg_end_flag_idx("beg", char_or_elem)
end_idx = self.get_beg_end_flag_idx("end", char_or_elem)
return [beg_idx, end_idx]
def get_beg_end_flag_idx(self, beg_or_end, char_or_elem):
if char_or_elem == "char":
if beg_or_end == "beg":
idx = self.dict_character[self.beg_str]
elif beg_or_end == "end":
idx = self.dict_character[self.end_str]
else:
assert False, "Unsupport type %s in get_beg_end_flag_idx of char" \
% beg_or_end
elif char_or_elem == "elem":
if beg_or_end == "beg":
idx = self.dict_elem[self.beg_str]
elif beg_or_end == "end":
idx = self.dict_elem[self.end_str]
else:
assert False, "Unsupport type %s in get_beg_end_flag_idx of elem" \
% beg_or_end
else:
assert False, "Unsupport type %s in char_or_elem" \
% char_or_elem
return idx
ppocr/utils/dict/table_dict.txt 0 → 100644
View file @ e93735a2
←
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ppocr/utils/dict/table_structure_dict.txt 0 → 100644
View file @ e93735a2
This diff is collapsed.
ppocr/utils/logging.py
View file @ e93735a2
...@@ -22,7 +22,7 @@ logger_initialized = {} ...@@ -22,7 +22,7 @@ logger_initialized = {}
@functools.lru_cache() @functools.lru_cache()
def get_logger(name='root', log_file=None, log_level=logging.INFO): def get_logger(name='root', log_file=None, log_level=logging.DEBUG):
"""Initialize and get a logger by name. """Initialize and get a logger by name.
If the logger has not been initialized, this method will initialize the If the logger has not been initialized, this method will initialize the
logger by adding one or two handlers, otherwise the initialized logger will logger by adding one or two handlers, otherwise the initialized logger will
......
ppocr/utils/network.py 0 → 100644
View file @ e93735a2
# copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import os
import sys
import tarfile
import requests
from tqdm import tqdm
from ppocr.utils.logging import get_logger
def download_with_progressbar(url, save_path):
logger = get_logger()
response = requests.get(url, stream=True)
total_size_in_bytes = int(response.headers.get('content-length', 0))
block_size = 1024 # 1 Kibibyte
progress_bar = tqdm(total=total_size_in_bytes, unit='iB', unit_scale=True)
with open(save_path, 'wb') as file:
for data in response.iter_content(block_size):
progress_bar.update(len(data))
file.write(data)
progress_bar.close()
if total_size_in_bytes == 0 or progress_bar.n != total_size_in_bytes:
logger.error("Something went wrong while downloading models")
sys.exit(0)
def maybe_download(model_storage_directory, url):
# using custom model
tar_file_name_list = [
'inference.pdiparams', 'inference.pdiparams.info', 'inference.pdmodel'
]
if not os.path.exists(
os.path.join(model_storage_directory, 'inference.pdiparams')
) or not os.path.exists(
os.path.join(model_storage_directory, 'inference.pdmodel')):
assert url.endswith('.tar'), 'Only supports tar compressed package'
tmp_path = os.path.join(model_storage_directory, url.split('/')[-1])
print('download {} to {}'.format(url, tmp_path))
os.makedirs(model_storage_directory, exist_ok=True)
download_with_progressbar(url, tmp_path)
with tarfile.open(tmp_path, 'r') as tarObj:
for member in tarObj.getmembers():
filename = None
for tar_file_name in tar_file_name_list:
if tar_file_name in member.name:
filename = tar_file_name
if filename is None:
continue
file = tarObj.extractfile(member)
with open(
os.path.join(model_storage_directory, filename),
'wb') as f:
f.write(file.read())
os.remove(tmp_path)
def is_link(s):
return s is not None and s.startswith('http')
def confirm_model_dir_url(model_dir, default_model_dir, default_url):
url = default_url
if model_dir is None or is_link(model_dir):
if is_link(model_dir):
url = model_dir
file_name = url.split('/')[-1][:-4]
model_dir = default_model_dir
model_dir = os.path.join(model_dir, file_name)
return model_dir, url
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